Procedia Computer Science

Procedia Computer Science 3 (2011) 276 281 Procedia Computer Science 00 (2010) 000 000 Procedia Computer Science www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia WCIT 2010 The critical factors impact on online customer satisfaction Chun-Chun Lin a*, Hsueh-Ying Wu b, Yong-Fu Chang c a The department of business administration, Far East University, No.49, Chung Hua Rd., Hsin-Shih. Tainan County 744, Taiwan b The department of knowledge management, Aletheia University on Matou Campus, No.70-11 Pei-Shi Liao, Matou, 721, Taiwan C College of commerce and management, Far East University, No. 49, Chung Hua Rd., Hsin-Shih. Tainan County 744, Taiwan Abstract In the last decade, the concepts of customer satisfaction and customer retention have gained increasing importance in both online and off-line businesses. The primary objective of the present study is intended to ascertain the factors that affect online consumers satisfaction in Taiwan. In it, information quality, system quality, service quality, product quality, delivery quality and perceived price have been identified and taken as the antecedents of user satisfaction. The present study, too, holds the key to unravelling how these factors may influence online consumers satisfaction. A survey was conducted with 390 Taiwan s university undergraduates who had online purchase experience. Multiple regression techniques were used to verify the overall model fit and to illustrate online customers satisfaction. The results showed that online consumers satisfaction was positive and significant affected by information quality, system quality, service quality, product quality, delivery quality and perceived price at significant P <0.01 level. Moreover, delivery quality was the most important factor and followed by product quality. The evidence generated in the present study suggests that e-commerce operators should pay more attention on the product sourcing, and cooperate with the delivery supplier to provide a higher delivery quality such as correct order, on time, and safety package. The implications of this finding, among others, are thoroughly discussed in the concluding section. c 2010 Published by Elsevier Ltd. Open access under CC BY-NC-ND license. Selection and/or peer-review under responsibility of the Guest Editor. Keywords: user satisfaction, information quality, system quality, service quality, product quality, delivery quality, perceived price. 1. Introduction Online customer retention has attracted considerable attention in recent years, partly because it serves as a means of gaining competitive advantage [28]. When a customer is satisfied with a particular internet store, he or she is more likely to shop there again [15]. Therefore, concepts of both customer satisfaction and customer retention have become increasingly important to online and off-line businesses. It is important to understand the factors that drive consumers satisfaction and their choice of the online channels [8]. Kolter [17] pointed out that the buying process includes problem/need recognition, information search, evaluation of alternatives, purchase decision, and post-purchase behavior. Satisfaction is the consequence of the customer s experience during various purchasing stages. Online customer shopping experience is based solely on online stores information because of a lack of physical contact [23]. Therefore, information as well as system and service quality may influence customers satisfaction during the information-search stage and shoppers purchase decisions. * Corresponding author. Tel.: +886-6-5979566# 5225; fax: +886-6-5977610. E-mail address: purelin@ms17.hinet.net. 1877-0509 c 2010 Published by Elsevier Ltd. Open access under CC BY-NC-ND license. doi:10.1016/j.procs.2010.12.047

C.-C. Lin et al. / Procedia Computer Science 3 (2011) 276 281 277 The present study focused on indentifying and measuring the constructs that may serve as the antecedents of online user satisfaction. This study further intended to verify empirically the relationship between these constructs and online user satisfaction. In doing so, this study synthesized the information-system research and the marketing perspectives while identifying instruments for measuring online user satisfaction and its antecedents. The survey targeted Taiwan s university undergraduates who had online shopping experience. 2. Specification of Online User Satisfaction Satisfaction is believed to influence attitude change and purchase intention [25]. A satisfactory purchase experience would appear to be one requirement for the type of continued interest in a product that might lead to repeat purchasing [7]. Many scholars found that satisfaction is one of critical factors influencing the continued purchase intentions [5, 8, 11, 12, 15, 24, 28, 30, 32]. In e-commerce context, DeLone and McLone [7] identified User Satisfaction as an important means of measuring our customers opinions of an e-commerce system. 3. Theoretical Framework Since the e-commerce should consider not only the information systems but also marketing strategies, this study reviewed the literature on both. Regarding the information systems field, this paper employed information quality, system quality, and service quality dimensions to investigate the consumers satisfaction with e-commerce based on the updated DeLone and McLean [7] information systems (D&M IS) success model. Regarding the marketing field, we introduced the product quality, delivery quality, and perceived price into our research model. 3.1. E-Commerce system quality Regarding the updated D & M IS success model, many researches employed information quality, system quality, or service quality dimension to investigate the consumers e-commerce behavior [3, 18, 19, 21, 22]. Lin [22] identified Web site quality dimension, including information quality, system quality, and service quality and emphasized that system quality, information quality, and service quality are important factors influencing customer satisfaction. In sum, according to the previous literature, information quality, system quality, and service quality are important independent variables of information system usage and user satisfaction. These three factors have been applied in many contexts. Therefore, this study proposes: H1. Information quality has a positive influence on online user satisfaction. H2. System quality has a positive influence on online user satisfaction. H3. Service quality has a positive influence on online user satisfaction. 3.2. Product Quality and Delivery Quality Perceived product quality is defined as the consumer s judgment about a product s overall excellence or superiority [6]. Keeney [14] indicated that minimizing product cost and maximizing product quality are major factors in e-commerce success. Patterson [27] pointed out that perceived product performance is the most powerful determinant on satisfaction. On the other hand, the delivery of a product can affect all fundamental objectives of the value proposition [14]. Ahn, Ryu, and Han [2] indicated that the timely and reliable delivery increase user satisfaction so that they will shop again. Thus, other hypotheses are: H4. Product quality has a positive influence on online user satisfaction. H5. Delivery quality has a positive influence on online user satisfaction.

278 C.-C. Lin et al. / Procedia Computer Science 3 (2011) 276 281 3.3. Perceived Price From the consumer s perspective, price is what is given up or scarified to obtain a product [33]. Gupta & Kim [9] defined perceived price as the level of (monetary) price at a vendor in comparison with the customer s reference price and found that the influence of perceived price on purchase intention loses strength with increased transaction experience. Cao & Gruca [4] examined the customer ratings of pre-purchase and post purchase service to explain price variations in the online book market and found that the higher prices of the three market leaders were most likely associated with higher satisfaction ratings of both pre- and post-purchase satisfaction. Therefore, another hypothesis is: H6. Perceived price has a positive influence on online user satisfaction. 4. Research Methodology The first step toward developing measurement involves identifying the operational definitions of the study constructs. The proposed conceptual model in the present study suggests that information quality, system quality, service quality, product quality, delivery quality, and perceived price are the independent variables while online user satisfaction is the dependent variable. The definitions of information quality and system quality were adapted from Delone and Mclean [7]. Service quality definition comes from Kim, Lee, & Law [16]. Definitions of product quality and delivery quality were adapted from Ahn et al. [2]. Perceived price definition comes from Gupta and Kim [9]. Definition of online user satisfaction was adapted from Delone and Mclean [7]. 4.1. Development of Measuring Instruments Based on previous research, the present study used survey methodology with questionnaire items measured on Likert scales. Most measuring instruments were adapted from validated measures, the IS success model, and the marketing research. All statements were rephrased to fit the context of the present study. Items for measuring information quality were adapted from Ahn et al. [2] and Kim et al. [16]. Items on system-quality instruments were adapted from Ahn et al. [2] and Brown and Jayakody [3]. Service quality items were adapted from Ahn et al. [3], Tsai and Huang [28], and Wang [29]. Product quality items were adapted from Ahn et al. [2], and Hult, Boyer, and Ketchen [13]. Delivery quality items were adapted from Ahn et al. [2]. Items measuring perceived price were adapted from Gupta and Kim [9] and Kim et al. [16]. User satisfaction items were adapted from Anderson and Srinivasan [1]. 4.2. Sampling procedure Participants in the present study were university undergraduates in Taiwan. Using university undergraduates is appropriate as they have good computer skills and have more frequent access to Internet than do other consumers [6]. Most university students are electronic service users [31]. The investigator distributed 390 questionnaires to students on campus face to face. Participants were asked to recall a recent on-line purchasing experience and refer to this experience when providing their answers. Surveys were collected immediately upon completion. Three out of all completed questionnaires were discarded because they were incomplete. 5. Data Analysis and Results The participants ranged from freshman to seniors and comprised 63.4% female and 36.4% male. Overall, 81.1% had more than 1 year of online purchasing experience, 70% spent less than 32USD and 1.8% more than 160USD on online shopping per month. This study conducted multiple regression method to test the hypotheses. The author employed the enter estimate procedure and assessing the model fit. The regression coefficients of the first five variables (product quality, system quality, information quality, perceived price, delivery quality) were significant at.001 level (p<0.001) and for the SRQ variable at.01 level (p<0.01). These six independent variables explained 62 percent variance in user

C.-C. Lin et al. / Procedia Computer Science 3 (2011) 276 281 279 satisfaction. The standardized coefficients were (0.188, 0.172, 0.156, 0.117, 0.203, and 0.162). Delivery quality, followed by product quality, was the most important factor. The overall online user satisfaction correlated positively and significantly with all six independent variables. All correlations were significant at 0.01 level. Hence, research hypotheses H1-H6 can be supported. 6. Conclusion and Managerial Implications Based on the findings of this research, user e-commerce satisfaction context relates to six factors: information quality, system quality, service quality, product quality, delivery quality, and perceived price. The e-commerce managers should development not only good information system features, that is, information quality, system quality, and service quality, but also marketing features, that is, product quality, delivery quality, and perceived price, which can influence user satisfaction positively. According to the findings of this study, the customers consider the product and delivery more important; thus, e- commerce proprietors should pay more attention to the product sourcing and cooperate with the delivery supplier to provide a higher quality of delivery, such as correct order, timeliness, and safety packaging. The implication for management is that customers sense of the good buy and worthy product or service is likely to influence satisfaction of online customers directly. Another implication is that when developing strategies to retain online customers, management needs to develop not only high quality e-commerce system but also quality products, reliable delivery, and fair price. 7. Limitations and Suggestions Although this study provides meaningful managerial implications, it has some limitations. First, the model was empirically tested in a sample of university undergraduates from Taiwan. Thus, it cannot be assumed that the sample is representative of the worldwide e-population. Past research has found that culture plays a significant role in consumer behaviors [10, 20]. Future research should replicate this study and test this conceptual model in different country or culture. Because the respondents in this study were university undergraduates, the items that they frequently bought were books, cloths, music, or movies, for example. The cost of these items is lower; therefore, the perceived price is no longer an issue for them. The results of this study cannot represent the customers who buy high cost items online, such as motorcycle, jewelry, or car, to mention a few. Future research may target the buyers of high cost items and explore the factors influencing their satisfaction. References 1. R.E. Anderson, and S.S. Srinivasan, E-satisfaction and e-loyalty: A contingency framework. Psychology & Marketing, 2003. 20(2): p. 123-38. 2. T. Ahn, S. Ryu, and I. Han, The impact of the online and offline features on the user acceptance of Internet shopping malls. Electronic Commerce Research and Applications, 2004. 3: p. 405-19. 3. I. Brown, and R. Jayakody, B2C e-commerce Success: a Test and Validation of a Revised Conceptual Model. Electronic Journal of Information Systems Evaluation, 2008. 11(3): p. 167-84. 4. Y. Cao, and T.S. Gruca, The influence of pre- and post-purchase service on prices in the online book market. Journal of Interactive Marketing, 2004. 18(4): p. 51-62. 5. R.T. Cenfetelli, I. Benbasat, and S. Al-Natour, Addressing the what and how of online services: Positioning supporting-services functionality and service quality for business-to-consumer success. Information Systems Research, 2008. 19(2): p. 161-81. 6. Z. Chen and A.J. Dubinsky, A conceptual model of perceived customer value in e-commerce: A preliminary investigation. Psychology & Marketing, 2003. 20(4): p. 323-47. 7. W.H. DeLone and E.R. McLean, The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems, 2003. 19(4): p. 9-30.

280 C.-C. Lin et al. / Procedia Computer Science 3 (2011) 276 281 8. S. Devaraj, M. Fan, and R. Kohli, Antecedents of B2C channel satisfaction and preference: validating e- commerce metrics. Information Systems Research, 2002. 13(3): p. 316-33. 9. S. Gupta and H.-W. Kim, The moderating effect of transaction experience on the decision calculus in on-line repurchase. International Journal of Electronic Commerce, 2007. 12(1): p. 127-58. 10.G. Hofstede, The cultural relativity of organizational practices and theories. Journal of International Business Studies (pre-1986), 1983. 14(000002): p. 75-89. 11. B.B. Holloway, S. Wang, and J.T. Parish, The role of cumulative online purchasing experience in service recovery management. Journal of Interactive Marketing, 2005. 19(3): p. 54-66. 12. M.-H. Hsu, et al., A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior. International Journal of Human-Computer Studies, 2006. 64(9): p. 889-904. 13. G.T.M. Hult, K.K. Boyer, and J. David J. Ketchen, Quality, operational logistics strategy, and repurchase intentions: A profile deviation analysis. Journal of Business Logistics, 2007. 28(2): p. 105-32. 14. R.L. Keeney, The value of Internet commerce to the customer. Management Science, 1999. 45(4): p. 533-42. 15. M. Khalifa and V. Liu, Online consumer retention: contingent effects of online shopping habit and online shopping experience. European Journal of Information Systems, 2007. 16(6): p. 780-92. 16. T.G. Kim, J.H. Lee, and R. Law, An empirical examination of the acceptance behaviour of hotel front office systems: An extended technology acceptance model. Tourism Management, 2008. 29(3): p. 500-13. 17. P. Kotler, Marketing Management: Analysis, Planning, Implementation, and Control 9th ed. 1997, NJ: Prentice Hall 18. H.-H. Kuan, G.-W. Bock, and V. Vathanophas, Comparing the effects of website quality on customer initial purchase and continued purchase at e-commerce websites. Behaviour & Information Technology, 2008. 27(1): p. 3-16. 19. Y. Lee and K.A. Kozar, Investigating the effect of website quality on e-business success: An analytic hierarchy process (AHP) approach. Decision Support Systems, 2006. 42(3): p. 1383-401. 20. Z. Liao and M.T. Cheung, Internet-based e-shopping and consumer attitudes: an empirical study. Information & Management, 2001. 38(5): p. 299-306. 21. Lin, H.-F. and G.-G. Lee, Determinants of success for online communities: an empirical study. Behaviour & Information Technology, 2006. 25(6): p. 479-88. 22. H.-F. Lin, The impact of Website quality dimensions on customer satisfaction in the B2C e-commerce context. Total Quality Management & Business Excellence, 2007. 18(4): p. 363-78. 23. V. McKinney, K. Yoon, and M.Z. Fatemeh, The measurement of Web-customer satisfaction: An expectation and disconfirmation approach. Information Systems Research, 2002. 13(3): p. 296-315. 24. L.K. Molinari, R. Abratt, and P. Dion, Satisfaction, quality and value and effects on repurchase and positive word-of-mouth behavioral intentions in a B2B services context. Journal of Services Marketing, 2008. 22(5): p. 363-73. 25. R.L. Oliver, A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research (JMR), 1980. 17(4): p. 460-69. 26. R.L. Oliver, Cognitive, affective, and attribute bases of the satisfaction response. Journal of Consumer Research, 1993. 20(3): p. 418-430. 27. P.G. Patterson, Expectations and product performance as determinants of satisfaction for a high-involvement purchase. Psychology & Marketing, 1993. 10(5): p. 449-65. 28. H.-T. Tsai and H.-C. Huang, Determinants of e-repurchase intentions: An integrative model of quadruple retention drivers. Information & Management, 2007. 44(3): p. 231-9. 29. Y.-S. Wang, Assessing e-commerce systems success: a respecification and validation of the Delone and Mclean model of IS success. Info Systems Journal, 2008. 18: p. 529-57. 30. C.-H. Yen and H.-P. Lu, Factors influencing online auction repurchase intention. Internet Research, 2008. 18(1): p. 7-25. 31. Y. Yi and T. Gong, The electronic service quality model: The moderating effect of customer self-efficacy. Psychology & Marketing, 2008. 25(7): p. 587-601. 32. J. J. Zboja and C.M. Voorhees, The impact of brand trust and satisfaction on retailer repurchase intentions. Journal of Services Marketing, 2002. 20(6): p.381-90.

C.-C. Lin et al. / Procedia Computer Science 3 (2011) 276 281 281 33. V.A. Zeithaml, Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, 1988. 52: p. 2-22.